Your browser doesn't support javascript.
loading
Show: 20 | 50 | 100
Results 1 - 4 de 4
Filter
Add more filters

Database
Language
Journal subject
Affiliation country
Publication year range
1.
Ann Med ; 56(1): 2317348, 2024 12.
Article in English | MEDLINE | ID: mdl-38364216

ABSTRACT

BACKGROUND: Lean individuals with non-alcohol fatty liver disease (NAFLD) often have normal body size but abnormal visceral fat. Therefore, an alternative to body mass index should be considered for prediction of lean-NAFLD. This study aimed to use representative visceral fat links with other laboratory parameters using the least absolute shrinkage and selection operator (LASSO) method to construct a predictive model for lean-NAFLD. METHODS: This retrospective cross-sectional analysis enrolled 2325 subjects with BMI < 24 kg/m2 from medical records of 51,271 examinees who underwent a routine health check-up. They were randomly divided into training and validation cohorts at a ratio of 1:1. The LASSO-derived prediction model used LASSO regression to select 23 clinical and laboratory factors. The discrimination and calibration abilities were evaluated using the Hosmer-Lemeshow test and calibration curves. The performance of the LASSO model was compared with the fatty liver index (FLI) model. RESULTS: The LASSO-derived model included four variables-visceral fat, triglyceride levels, HDL-C-C levels, and waist hip ratio-and demonstrated superior performance in predicting lean-NAFLD with high discriminatory ability (AUC, 0.8416; 95% CI: 0.811-0.872) that was comparable with the FLI model. Using a cut-off of 0.1484, moderate sensitivity (75.69%) and specificity (79.86%), as well as high negative predictive value (95.9%), were achieved in the LASSO model. In addition, with normal WC subgroup analysis, the LASSO model exhibits a trend of higher accuracy compared to FLI (cut-off 15.45). CONCLUSIONS: We developed a LASSO-derived predictive model with the potential for use as an alternative tool for predicting lean-NAFLD in clinical settings.


Researchers developed a model to predict a type of liver disease called non-alcoholic fatty liver disease (NAFLD) in lean individuals.The model accurately detects NAFLD in lean individuals using factors like visceral fat, triglyceride levels, and waist-to-hip ratio, aiding in identifying the disease in normal-weight people with abnormal fat distribution.


Subject(s)
Non-alcoholic Fatty Liver Disease , Humans , Non-alcoholic Fatty Liver Disease/diagnosis , Cross-Sectional Studies , Retrospective Studies , Liver Function Tests , Body Mass Index
2.
Diagnostics (Basel) ; 14(8)2024 Apr 09.
Article in English | MEDLINE | ID: mdl-38667430

ABSTRACT

Low-dose computed tomography screening for lung cancer is currently targeted at heavy smokers or those with a family history of lung cancer. This study aimed to identify risk factors for lung cancer in individuals who do not meet the current lung cancer screening criteria as stipulated by the Taiwan Health Promotion Agency's low-dose computed tomography (LDCT) screening policy. A cohort analysis was conducted on 12,542 asymptomatic healthy subjects aged 20-80 years old who voluntarily underwent LDCT scans from January 2016 to December 2021. Logistic regression demonstrated that several factors, including age over 55 years, female gender, a body mass index (BMI) less than 23, a previous history of respiratory diseases such as tuberculosis or obstructive respiratory diseases (chronic obstructive pulmonary disease [COPD], asthma), and previous respiratory symptoms such as cough or dyspnea, were associated with high-risk lung radiology scores according to LDCT scans. These findings indicate that risk-based assessments using primary data and questionnaires to identify risk factors other than heavy smoking and a family history of lung cancer may improve the efficiency of lung cancer screening.

3.
J Chin Med Assoc ; 87(2): 171-178, 2024 Feb 01.
Article in English | MEDLINE | ID: mdl-38099672

ABSTRACT

BACKGROUND: Hepatocellular carcinoma (HCC) with major portal vein invasion (MPVI) presents very poor outcomes. Hepatic artery infusion chemotherapy (HAIC) and radiation therapy (RT) have both been found to be effective for advanced HCC. In this retrospective study, we compared the therapeutic outcomes of our "new" HAIC regimen with and without concurrent RT, before and after propensity score matching (PSM) in treating HCC patients with MPVI. METHODS: One hundred forty patients with MPVI received HAIC alone and 35 patients underwent concurrent HAIC and RT during a 16-year period. The left subclavian artery was adopted as the entry site for a temporary catheter placement for a 5-day chemoinfusion. The Modified Response Evaluation Criteria in Solid Tumors (mRECIST) was adopted to assess the objective response rate (ORR). The Kaplan-Meier curve was used to calculate progression-free survival (PFS) and overall survival (OS) between the two groups. Univariate and multivariate analyses by Cox regression model were used to assess hazard ratios. RESULTS: Of the 140 patients with Child-Pugh A liver function, the median OS was 17.0 months. In the initial cohort, higher ORR and PFS were found in the concurrent RT group than in the HAIC alone group (80% vs 66.4% and 9 vs 8 months, respectively) but shorter OS (10.5 vs 14.5 months, p = 0.039) was observed. After PSM, the OS was 10 and 15 months ( p = 0.012), respectively. Multivariable Cox regression analysis revealed that the significant factors for adjusting hazard ratios for OS were Child-Pugh classification, alpha fetal protein (AFP) level, and hepatic vein invasion. CONCLUSION: HAIC is an effective treatment for advanced HCC patients with MPVI. Concurrent HAIC and full-dose RT were associated with worse clinical outcomes.


Subject(s)
Carcinoma, Hepatocellular , Liver Neoplasms , Humans , Carcinoma, Hepatocellular/radiotherapy , Carcinoma, Hepatocellular/drug therapy , Liver Neoplasms/pathology , Portal Vein/pathology , Retrospective Studies , Treatment Outcome , Antineoplastic Combined Chemotherapy Protocols/adverse effects
SELECTION OF CITATIONS
SEARCH DETAIL